Overview

Dataset statistics

Number of variables9
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory81.1 B

Variable types

DateTime1
Numeric5
Categorical3

Dataset

Description인구동태 입력 현황에 대한 데이터로 출생, 사망, 혼인, 이혼, 기아발견, 실종선고, 혼인취소 등의 항목을 제공합니다.
Author경기도 남양주시
URLhttps://www.data.go.kr/data/15069521/fileData.do

Alerts

데이터기준일 has constant value ""Constant
출생 is highly overall correlated with 사망 and 2 other fieldsHigh correlation
사망 is highly overall correlated with 출생 and 2 other fieldsHigh correlation
혼인 is highly overall correlated with 이혼 and 2 other fieldsHigh correlation
이혼 is highly overall correlated with 출생 and 3 other fieldsHigh correlation
실종선고 is highly overall correlated with 사망 and 2 other fieldsHigh correlation
혼인취소 is highly overall correlated with 출생 and 1 other fieldsHigh correlation
혼인취소 is highly imbalanced (71.7%)Imbalance
날짜 has unique valuesUnique
출생 has 7 (11.5%) zerosZeros
혼인 has 24 (39.3%) zerosZeros
실종선고 has 18 (29.5%) zerosZeros

Reproduction

Analysis started2024-03-14 14:13:37.178895
Analysis finished2024-03-14 14:13:44.423696
Duration7.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Date

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size616.0 B
Minimum2014-08-01 00:00:00
Maximum2023-12-01 00:00:00
2024-03-14T23:13:44.618186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:45.057827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

출생
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201.7541
Minimum0
Maximum482
Zeros7
Zeros (%)11.5%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-14T23:13:45.466634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median251
Q3301
95-th percentile477
Maximum482
Range482
Interquartile range (IQR)299

Descriptive statistics

Standard deviation178.48545
Coefficient of variation (CV)0.88466826
Kurtosis-1.419556
Mean201.7541
Median Absolute Deviation (MAD)207
Skewness0.10365339
Sum12307
Variance31857.055
MonotonicityNot monotonic
2024-03-14T23:13:45.884611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 7
 
11.5%
2 5
 
8.2%
1 5
 
8.2%
4 4
 
6.6%
3 2
 
3.3%
301 2
 
3.3%
432 2
 
3.3%
232 2
 
3.3%
262 2
 
3.3%
270 2
 
3.3%
Other values (28) 28
45.9%
ValueCountFrequency (%)
0 7
11.5%
1 5
8.2%
2 5
8.2%
3 2
 
3.3%
4 4
6.6%
5 1
 
1.6%
229 1
 
1.6%
232 2
 
3.3%
235 1
 
1.6%
240 1
 
1.6%
ValueCountFrequency (%)
482 1
1.6%
481 1
1.6%
480 1
1.6%
477 1
1.6%
472 1
1.6%
467 1
1.6%
458 1
1.6%
452 1
1.6%
443 1
1.6%
432 2
3.3%

사망
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.7541
Minimum13
Maximum338
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-14T23:13:46.278783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile18
Q123
median212
Q3252
95-th percentile281
Maximum338
Range325
Interquartile range (IQR)229

Descriptive statistics

Standard deviation112.30534
Coefficient of variation (CV)0.71644274
Kurtosis-1.7433594
Mean156.7541
Median Absolute Deviation (MAD)58
Skewness-0.29998854
Sum9562
Variance12612.489
MonotonicityNot monotonic
2024-03-14T23:13:46.708596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
23 4
 
6.6%
21 3
 
4.9%
18 3
 
4.9%
206 3
 
4.9%
240 3
 
4.9%
260 2
 
3.3%
19 2
 
3.3%
25 2
 
3.3%
255 2
 
3.3%
20 2
 
3.3%
Other values (35) 35
57.4%
ValueCountFrequency (%)
13 1
 
1.6%
14 1
 
1.6%
16 1
 
1.6%
18 3
4.9%
19 2
3.3%
20 2
3.3%
21 3
4.9%
23 4
6.6%
25 2
3.3%
26 1
 
1.6%
ValueCountFrequency (%)
338 1
1.6%
301 1
1.6%
297 1
1.6%
281 1
1.6%
274 1
1.6%
272 1
1.6%
270 1
1.6%
264 1
1.6%
263 1
1.6%
261 1
1.6%

혼인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.655738
Minimum0
Maximum280
Zeros24
Zeros (%)39.3%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-14T23:13:47.090124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median79
Q3109
95-th percentile252
Maximum280
Range280
Interquartile range (IQR)109

Descriptive statistics

Standard deviation84.731318
Coefficient of variation (CV)1.0376652
Kurtosis-0.35689118
Mean81.655738
Median Absolute Deviation (MAD)79
Skewness0.80644733
Sum4981
Variance7179.3962
MonotonicityNot monotonic
2024-03-14T23:13:47.471116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 24
39.3%
86 2
 
3.3%
88 2
 
3.3%
169 2
 
3.3%
109 2
 
3.3%
71 2
 
3.3%
96 1
 
1.6%
79 1
 
1.6%
178 1
 
1.6%
73 1
 
1.6%
Other values (23) 23
37.7%
ValueCountFrequency (%)
0 24
39.3%
65 1
 
1.6%
71 2
 
3.3%
72 1
 
1.6%
73 1
 
1.6%
78 1
 
1.6%
79 1
 
1.6%
81 1
 
1.6%
82 1
 
1.6%
84 1
 
1.6%
ValueCountFrequency (%)
280 1
1.6%
263 1
1.6%
254 1
1.6%
252 1
1.6%
247 1
1.6%
237 1
1.6%
217 1
1.6%
209 1
1.6%
198 1
1.6%
180 1
1.6%

이혼
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.09836
Minimum41
Maximum209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-14T23:13:47.862528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41
5-th percentile55
Q169
median112
Q3145
95-th percentile164
Maximum209
Range168
Interquartile range (IQR)76

Descriptive statistics

Standard deviation42.867122
Coefficient of variation (CV)0.39292178
Kurtosis-1.0621174
Mean109.09836
Median Absolute Deviation (MAD)41
Skewness0.16496444
Sum6655
Variance1837.5902
MonotonicityNot monotonic
2024-03-14T23:13:48.295662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
70 3
 
4.9%
55 3
 
4.9%
134 2
 
3.3%
153 2
 
3.3%
143 2
 
3.3%
164 2
 
3.3%
145 2
 
3.3%
113 2
 
3.3%
110 2
 
3.3%
146 2
 
3.3%
Other values (36) 39
63.9%
ValueCountFrequency (%)
41 1
 
1.6%
43 1
 
1.6%
54 1
 
1.6%
55 3
4.9%
56 1
 
1.6%
58 1
 
1.6%
59 1
 
1.6%
62 2
3.3%
64 1
 
1.6%
65 1
 
1.6%
ValueCountFrequency (%)
209 1
1.6%
200 1
1.6%
168 1
1.6%
164 2
3.3%
160 1
1.6%
157 1
1.6%
155 1
1.6%
154 1
1.6%
153 2
3.3%
151 1
1.6%

기아발견
Categorical

Distinct5
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size616.0 B
0
43 
2
9 
1
7 
3
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
70.5%
2 9
 
14.8%
1 7
 
11.5%
3 1
 
1.6%
5 1
 
1.6%

Length

2024-03-14T23:13:48.709841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:13:49.035054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
70.5%
2 9
 
14.8%
1 7
 
11.5%
3 1
 
1.6%
5 1
 
1.6%

실종선고
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.295082
Minimum0
Maximum129
Zeros18
Zeros (%)29.5%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-14T23:13:49.377551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q394
95-th percentile120
Maximum129
Range129
Interquartile range (IQR)94

Descriptive statistics

Standard deviation50.20204
Coefficient of variation (CV)1.2458602
Kurtosis-1.6033886
Mean40.295082
Median Absolute Deviation (MAD)2
Skewness0.55654951
Sum2458
Variance2520.2448
MonotonicityNot monotonic
2024-03-14T23:13:49.796541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 18
29.5%
1 11
18.0%
2 5
 
8.2%
115 2
 
3.3%
120 2
 
3.3%
94 2
 
3.3%
109 1
 
1.6%
3 1
 
1.6%
108 1
 
1.6%
81 1
 
1.6%
Other values (17) 17
27.9%
ValueCountFrequency (%)
0 18
29.5%
1 11
18.0%
2 5
 
8.2%
3 1
 
1.6%
5 1
 
1.6%
6 1
 
1.6%
68 1
 
1.6%
80 1
 
1.6%
81 1
 
1.6%
82 1
 
1.6%
ValueCountFrequency (%)
129 1
1.6%
121 1
1.6%
120 2
3.3%
115 2
3.3%
111 1
1.6%
109 1
1.6%
108 1
1.6%
107 1
1.6%
106 1
1.6%
102 1
1.6%

혼인취소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size616.0 B
0
58 
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 58
95.1%
1 3
 
4.9%

Length

2024-03-14T23:13:50.207536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:13:50.524170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 58
95.1%
1 3
 
4.9%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size616.0 B
2024-01-01
61 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-01
2nd row2024-01-01
3rd row2024-01-01
4th row2024-01-01
5th row2024-01-01

Common Values

ValueCountFrequency (%)
2024-01-01 61
100.0%

Length

2024-03-14T23:13:50.859626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:13:51.169003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-01 61
100.0%

Interactions

2024-03-14T23:13:42.558959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:37.510187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:38.729353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:40.184729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:41.392005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:42.720762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:37.752666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:38.974723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:40.419235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:41.635766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:42.976330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:38.004967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:39.231848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:40.667710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:41.889201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:43.214983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:38.240524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:39.475923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:40.900239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:42.131435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:43.465410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:38.486663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:39.929263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:41.144551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:13:42.378760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:13:51.542810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
날짜출생사망혼인이혼기아발견실종선고혼인취소
날짜1.0001.0001.0001.0001.0001.0001.0001.000
출생1.0001.0000.9110.7920.7820.5190.7930.715
사망1.0000.9111.0000.7410.7230.4840.8550.698
혼인1.0000.7920.7411.0000.7390.3590.5060.758
이혼1.0000.7820.7230.7391.0000.5010.6050.396
기아발견1.0000.5190.4840.3590.5011.0000.6240.000
실종선고1.0000.7930.8550.5060.6050.6241.0000.000
혼인취소1.0000.7150.6980.7580.3960.0000.0001.000
2024-03-14T23:13:51.825887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
혼인취소기아발견
혼인취소1.0000.000
기아발견0.0001.000
2024-03-14T23:13:52.073160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출생사망혼인이혼실종선고기아발견혼인취소
출생1.0000.6270.1500.6010.2270.3790.509
사망0.6271.000-0.4920.8210.6430.3490.495
혼인0.150-0.4921.000-0.535-0.7500.2190.551
이혼0.6010.821-0.5351.0000.6840.3030.370
실종선고0.2270.643-0.7500.6841.0000.4780.000
기아발견0.3790.3490.2190.3030.4781.0000.000
혼인취소0.5090.4950.5510.3700.0000.0001.000

Missing values

2024-03-14T23:13:43.814975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:13:44.254702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

날짜출생사망혼인이혼기아발견실종선고혼인취소데이터기준일
02023-1222186700202024-01-01
12023-11123104550002024-01-01
22023-1022986640002024-01-01
32023-0921973670102024-01-01
42023-0802079850102024-01-01
52023-0701671700602024-01-01
62023-0612371690202024-01-01
72023-0502096730002024-01-01
82023-0442565710102024-01-01
92023-0301894620202024-01-01
날짜출생사망혼인이혼기아발견실종선고혼인취소데이터기준일
512015-05430217247930102024-01-01
522015-044822532091130002024-01-01
532015-034802552541080302024-01-01
542015-02477236180910002024-01-01
552015-014672242631090202024-01-01
562014-124812092801340102024-01-01
572014-114222062171150102024-01-01
582014-104322061691370012024-01-01
592014-094322061691370012024-01-01
602014-084521961781230202024-01-01